Protein function prediction and classification using deep learning models and knowledge graph mining

IBSE is pleased to invite you to the 16th IBSE Colloquium. In this instance Professor Dr. Kannan will talk about “Protein function prediction and classification using deep learning models and knowledge graph mining”.

Abstract: Proteins are essential biological macromolecules that perform a wide range of cellular functions. Accurately predicting these functions is a significant challenge in bioinformatics and biotechnology. In this talk, I will share our recent advancements in predicting protein functions by combining deep learning, knowledge graph mining, and experimental techniques. Firstly, I will introduce Phosformer, a Transformer-based architecture based on protein language models to predict kinase-substrate interactions at the proteome scale. I will showcase how these methods can be applied to model large protein families effectively. Next, I will present a novel, scalable graph embedding approach for function prediction using network context within knowledge graphs. This involves integrating and conceptualizing data on protein evolutionary, structural, and functional properties into a comprehensive, human- and machine-readable knowledge graph. Finally, I will discuss new training opportunities for graduate students and post-docs interested in bioinformatics, glycobiology, and machine learning, highlighting how they can get involved in this cutting-edge research.

Speaker: Dr. Kannan is Professor of Biochemistry& Molecular Biology and the Institute of Bioinformatics at the University of Georgia, USA. His research encompasses mapping genome-phenome relationships in biomedically important protein families through the integration of quantitative and experimental approaches. He has published over 100 peer-reviewed articles in the areas of protein biophysics and bioinformatics with over 4,000 citations. He has trained over 50 undergraduate, graduate, post-graduate trainees, junior scientists and young investigators. He is the recipient of multiple state and national awards including the Georgia Coalition Distinguished Scholar Award, National Science Foundation CAREER award, NIH Maximizing Research Investigator Award and UGA Creative Research medal award.